In this paper, the output-oriented weight restricted comprehensive super efficiency DEA model and the projection concept is proposed, in the view of traditional DEA model can not distinguish between efficiency decision making units and the super efficiency DEA model does not consider the preference of the decision maker. The relationship between the output-oriented weight restricted comprehensive super efficiency DEA model and other super efficiency DEA models is discussed. Secondly, the relationship between the optimal objective function value of the output-oriented weight restricted comprehensive super efficiency DEA model and the effectiveness of decision making unit is analyzed. The relationship between the output-oriented weight restricted comprehensive super efficiency projection and the non-dominated solution of multi-objective programming is discussed. Finally, the scientific and technological innovation efficiency of industrial enterprises in 12 regions of western China is evaluated, and the method proposed in this paper is compared with the original methods. It is concluded that the method proposed in this paper is more advantageous and reasonable.
[1] Charnes A, Cooper W W, Rohodes E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6):429-444.
[2] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J]. Management Science, 1984, 30(9):1078-1092.
[3] Fare R, Grosskopf S. A nonparametric cost approach to scale efficiency[J]. Scandinavian Journal of Economics, 1985, 87(4):594õ604.
[4] Seiford L M, Thrall R M. Recent development in DEA. The mathematical programming approach to frontier analysis[J]. Journal of Economics, 1990, 46(1-2):7-38.
[5] Charnes A, Cooper W W, Wei Q L. A semi-infinite multi-criteria programming approach to data envelopment analysis with infinitely many decision making units[R]. The University of Texas at Austin, Center for Cybernetic Studies Report, CCS 551 September, 1986.
[6] Charnes A, Cooper W W, Wei Q L, et al. Cone ratio data envelopment analysis method and multi-objective programming[J]. International Journal of Systems Science, 1989, 20(7):1099-1118.
[7] 魏权龄. 评价相对有效性的数据包络分析模型[M].北京:中国人民大学出版社,2012.
[8] Andersen P, Petersen N C. A procedure for ranking efficient units in data envelopment analysis[J]. Management Science, 1993, 39, 1261-1264.
[9] 马占新. 广义数据包络分析方法[M]. 北京:科学出版社,2012.
[10] 马占新. 一种基于样本前沿面的综合评价方法[J]. 内蒙古大学学报, 2002, 33(6):606õ610.
[11] 马占新, 马生昀. 基于C2W模型的样本数据包络分析方法研究[J]. 系统工程与电子技术, 2009, 31(2):366õ372.
[12] 马占新, 马生昀. 基于C2WY模型的广义数据包络分析方法研究[J]. 系统工程学报, 2011, 26(2):251-261.
[13] Mu R, Ma Z X, Cui W. Fuzzy data envelopment analysis approach based on sample decision making units[J]. Systems Engineering and Electronics, 2012, 23(3):399-407.
[14] 马生昀, 马占新. 基于C2W模型的广义数据包络分析方法[J]. 系统工程理论与实践, 2014, 34(4):899-909.
[15] 马生昀, 马占新. 基于样本前沿面移动的广义DEA有效性排序[J]. 系统工程学报, 2014, 29(4):443-457.
[16] 晏蒙, 孟令杰. 基于DEA方法的中国工业科技创新效率分析[J]. 中国管理科学, 2015, 23卷专辑:77-82.
[17] 乌兰, 伊茹. 中国西部地区大中型工业企业技术创新效率评价[J]. 中央财经大学学报, 2013, 10:86-90.
